metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-small-UnidicBpe2
results: []
bert-small-UnidicBpe2
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5693
- Accuracy: 0.6686
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 256
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 768
- total_eval_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 14.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0974 | 1.0 | 69473 | 1.9746 | 0.6071 |
| 1.9586 | 2.0 | 138946 | 1.8301 | 0.6284 |
| 1.889 | 3.0 | 208419 | 1.7627 | 0.6383 |
| 1.8496 | 4.0 | 277892 | 1.7236 | 0.6442 |
| 1.8188 | 5.0 | 347365 | 1.6924 | 0.6490 |
| 1.7983 | 6.0 | 416838 | 1.6650 | 0.6535 |
| 1.7788 | 7.0 | 486311 | 1.6484 | 0.6558 |
| 1.7623 | 8.0 | 555784 | 1.6328 | 0.6580 |
| 1.7497 | 9.0 | 625257 | 1.6182 | 0.6605 |
| 1.7321 | 10.0 | 694730 | 1.6064 | 0.6623 |
| 1.7225 | 11.0 | 764203 | 1.5908 | 0.6647 |
| 1.707 | 12.0 | 833676 | 1.5859 | 0.6660 |
| 1.7049 | 13.0 | 903149 | 1.5752 | 0.6672 |
| 1.6982 | 14.0 | 972622 | 1.5693 | 0.6686 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.12.0+cu116
- Datasets 2.9.0
- Tokenizers 0.12.1